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Prediction of Alzheimer's Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data.


ABSTRACT: Alzheimer's disease (AD) is the most common cause of dementia. It is the fifth leading cause of death among elderly people. With high genetic heritability (79%), finding the disease's causal genes is a crucial step in finding a treatment for AD. Following the International Genomics of Alzheimer's Project (IGAP), many disease-associated genes have been identified; however, we do not have enough knowledge about how those disease-associated genes affect gene expression and disease-related pathways. We integrated GWAS summary data from IGAP and five different expression-level data by using the transcriptome-wide association study method and identified 15 disease-causal genes under strict multiple testing (? < 0.05), and four genes are newly identified. We identified an additional 29 potential disease-causal genes under a false discovery rate (? < 0.05), and 21 of them are newly identified. Many genes we identified are also associated with an autoimmune disorder.

SUBMITTER: Hao S 

PROVIDER: S-EPMC6330278 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Prediction of Alzheimer's Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data.

Hao Sicheng S   Wang Rui R   Zhang Yu Y   Zhan Hui H  

Frontiers in genetics 20190107


Alzheimer's disease (AD) is the most common cause of dementia. It is the fifth leading cause of death among elderly people. With high genetic heritability (79%), finding the disease's causal genes is a crucial step in finding a treatment for AD. Following the International Genomics of Alzheimer's Project (IGAP), many disease-associated genes have been identified; however, we do not have enough knowledge about how those disease-associated genes affect gene expression and disease-related pathways.  ...[more]

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